{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Kobayashi E"],"funding":["BLRD VA","NIBIB NIH HHS","Division of Diabetes, Endocrinology, and Metabolic Diseases","NIDDK NIH HHS","Veterans Affairs San Diego Healthcare System","National Institute of Biomedical Imaging and Bioengineering"],"pagination":["1704-1712"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12451836"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["48(10)"],"pubmed_abstract":["<h4>Objective</h4>Type 2 diabetes (T2D) and its associated complications develop heterogeneously over decades, but few studies span the progression from prediabetes to clinical events. We investigated whether long-term metabolic trajectories beginning in prediabetes delineate subgroups with differential complication risk.<h4>Research design and methods</h4>Clinical data from 1,732 Diabetes Prevention Program/Outcomes Study participants (follow-up 19 years) were analyzed across 12 phenotypes. Tensor decomposition was used to capture longitudinal patterns, and Gaussian mixture modeling was used to define longitudinal clusters. Cluster-specific complications were quantified with Cox and logistic regression.<h4>Results</h4>Four clusters emerged. Clusters 1 and 2 (73% of participants) maintaine"],"journal":["Diabetes care"],"pubmed_title":["Longitudinal Metabolic Trajectories in Diabetes Prevention Program Participants Reveal Subgroups With Varying Micro- and Macrovascular Complication Risks."],"pmcid":["PMC12451836"],"funding_grant_id":["U01 DK048407","R01DK123422","U01 DK048404","U01 DK048349","1I01BX006293","U01 DK048406","U01 DK048443","R01DK129840","U01 DK048400","U01 DK048489","T32 EB009380","U01 DK048468","R01 DK129840","U01 DK048485","U01 DK048387","U01 DK048380","U01 DK048381","T32EB9380","R01 DK123422","U01 DK048514","U01 DK048437","U01 DK048339","U01 DK048377","U01 DK048411","U01 DK048412","U01 DK048434","U01 DK048413","U01 DK048397","U01 DK048375","I01 BX006293"],"pubmed_authors":["Caro JF","Laferrere B","Testaverde L","Horse E","Hill Golden S","Kellum T","Smith CF","Boggs G","Johnson MK","Brancati FL","Percy CA","Enote A","Smith CM","Kavena K","Leon L","Sewenemewa J","Roston S","Ngo K","Rochon J","Heard D","Ryder 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R"],"additional_accession":[]},"is_claimable":false,"name":"Longitudinal Metabolic Trajectories in Diabetes Prevention Program Participants Reveal Subgroups With Varying Micro- and Macrovascular Complication Risks.","description":"<h4>Objective</h4>Type 2 diabetes (T2D) and its associated complications develop heterogeneously over decades, but few studies span the progression from prediabetes to clinical events. We investigated whether long-term metabolic trajectories beginning in prediabetes delineate subgroups with differential complication risk.<h4>Research design and methods</h4>Clinical data from 1,732 Diabetes Prevention Program/Outcomes Study participants (follow-up 19 years) were analyzed across 12 phenotypes. Tensor decomposition was used to capture longitudinal patterns, and Gaussian mixture modeling was used to define longitudinal clusters. Cluster-specific complications were quantified with Cox and logistic regression.<h4>Results</h4>Four clusters emerged. Clusters 1 and 2 (73% of participants) maintaine","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Oct","modification":"2026-04-30T03:16:08.902Z","creation":"2026-04-30T03:11:19.716Z"},"accession":"S-EPMC12451836","cross_references":{"pubmed":["40857122"],"doi":["10.2337/dc25-0866"]}}